What Went Wrong...
Examining the missteps of various software products across industries reveals common pitfalls that can derail even the most promising innovations. From inadequate market research and poor user experience design to insufficient testing and failure to adapt to technological advancements, these challenges underscore the importance of thorough planning and execution. The following section outlines specific cases, offering insights into how these factors contributed to their downfall and the lessons that can be gleaned to inform future endeavors.
Available Lessons:
200
Waze Carpool
TravelTech
Waze (Google)
The carpooling feature failed to scale due to limited adoption and difficulty in matching riders and drivers effectively.
WHAT WENT WRONG
Poor matching algorithms for ride requests
Limited awareness and promotion in key markets
SIGNALS MISSED
Low match success rates in pilot regions
User complaints about waiting times and cancellations
HOW COULD THEY HAVE AVOIDED THIS
Improving matching algorithms with user feedback
Conducting targeted campaigns to increase awareness
TEAMS INVOLVED
Product, Marketing, Engineering, Customer Success
Priceline Negotiator App
TravelTech
Priceline
An app allowing users to negotiate hotel prices failed due to a clunky interface and limited hotel participation.
WHAT WENT WRONG
Poor user experience in the negotiation flow
Weak partnerships with hotels for participation
SIGNALS MISSED
Negative feedback from users about the negotiation process
Low hotel engagement with the feature
HOW COULD THEY HAVE AVOIDED THIS
Simplifying the negotiation process for users
Strengthening hotel partnerships before launch
TEAMS INVOLVED
Product, Sales, Engineering, Customer Success
Orbitz Rewards App
TravelTech
Orbitz
The rewards app failed to engage users due to poor rewards value and limited redemption options.
WHAT WENT WRONG
Lack of valuable incentives for frequent travelers
Limited partnerships for rewards redemption
SIGNALS MISSED
User feedback indicating low perceived rewards value
Poor app engagement and retention metrics
HOW COULD THEY HAVE AVOIDED THIS
Partnering with more travel brands for better rewards options
Offering tiered rewards programs for frequent users
TEAMS INVOLVED
Product, Marketing, Sales, Customer Success
Farecast Price Predictor
TravelTech
Farecast (later Bing Travel)
Promised accurate airfare predictions but struggled due to frequent inaccuracies and poor user trust.
WHAT WENT WRONG
Weak algorithms for long-term price predictions
Limited data sources for regional markets
SIGNALS MISSED
High complaints about incorrect predictions
Declining user engagement over time
HOW COULD THEY HAVE AVOIDED THIS
Refining prediction models with diverse data inputs
Communicating prediction accuracy rates transparently
TEAMS INVOLVED
Product, Data, Engineering, Marketing
Ryanair Website Overhaul (2000s)
TravelTech
Ryanair
An early website overhaul aimed at simplifying bookings led to confusion and dropped transactions due to poor usability testing.
WHAT WENT WRONG
Poor design decisions without user testing
Technical bugs during payment processing
SIGNALS MISSED
High abandonment rates at checkout
Customer complaints about unclear navigation
HOW COULD THEY HAVE AVOIDED THIS
Conducting usability tests with real customers
Phased rollout with rigorous QA testing
TEAMS INVOLVED
Product, Design, Engineering, QA
Hopper Price Freeze
TravelTech
Hopper
A feature that allowed users to lock in prices for future bookings faced issues with inaccurate predictions and low adoption.
WHAT WENT WRONG
Poor algorithmic accuracy for price predictions
Limited trust from users in the feature’s reliability
SIGNALS MISSED
Complaints about price discrepancies after freezing
Low conversion rates for price freeze purchases
HOW COULD THEY HAVE AVOIDED THIS
Improving prediction algorithms with historical and real-time data
Building user trust through transparent communication
TEAMS INVOLVED
Product, Data, Engineering, Marketing